Cloud computing is increasingly being explored
as a cost effective alternative and addition to supercomputers
for some High Performance Computing (HPC) applications.
However, dynamic environment and interference by other
virtual machines are some of the factors which prevent efficient
execution of HPC applications in cloud.
Through this research, we leverage a message driven adaptive
runtime system to develop techniques that reduce the
gap between application performance on cloud and supercomputers.
Our scheme uses object migration to achieve load
balance for tightly coupled parallel applications executing in
virtualized environments that suffer from interfering jobs.
While restoring load balance, it not only reduces the timing
penalty caused by interfering jobs, but also reduces energy
consumption significantly. With experimental evaluation using
benchmarks and a real HPC application, we demonstrate that
our scheme reduces the timing penalty and energy overhead
associated with interfering jobs by at least 50%.